HPLC: compare fermentation profiles of different samples

Introduction

The goal of this analysis is to compare the fermentation profiles of HPLC samples.

Setup

Libraries

rm(list = ls());

library(knitr);
knitr::opts_chunk$set(warning = F, message = F);

library(stringr);
library(tidyverse);
library(readr);
library(gridExtra);
library(readxl);
library(plotly);


mytheme = theme(axis.text.x = element_text(size = 6), 
                axis.text.y = element_text(size = 6), 
                axis.title.x = element_text(size = 8), 
                axis.title.y = element_text(size = 8),
                strip.text.x = element_text(size = 6),
                legend.position = "none", 
                aspect.ratio =0.5,
                plot.title = element_text(size = 8),
               );

File IO

# input: directory to read sample information file
info.file = "/home/tolonen/Github/actolonen/Public/Analysis_Lab/Metabolites/HPLC/Analysis/Data/information_HPLC_DATE.xlsx";

# input fermentation measurements
data.file = "/home/tolonen/Github/actolonen/Public/Analysis_Lab/Metabolites/HPLC/Analysis/Data/Analysis/compound_concentrations.tsv";
data.in = read_tsv(file = data.file, col_names=T);

Methods

Select which detector to use for quantification of each acid

# Select RID by removing formate UV210, Actate UV210, Lactate RID
data.in = data.in %>%
  filter(!(Compound =="Formate" & Detector == "SPD-20A 210nm")) %>%
  filter(!(Compound =="Acetate" & Detector == "SPD-20A 210nm")) %>%
  filter(!(Compound =="Lactate" & Detector == "SPD-20A 210nm"));

Organize data for plotting

# focus on data of interest
data.all = data.in %>%
  filter(!grepl("H2SO4", Description)) %>%
  filter(!grepl("test", Description));

data.all = data.all %>%
  mutate(Strain_type = if_else(grepl("WT|GS2", Description), true = "control", false = "Test")) %>%
  mutate(Temp = Description) %>%
  separate(Temp, c("Strain", "Rep", "Treatment"), sep = "-");
  
# organize samples
data.samples = data.all %>%
  group_by(Sample, Compound) %>%
    mutate(Concentration_mean = mean(Concentration)) %>%
  ungroup() %>%
  dplyr::select(Compound, Concentration_mean, Sample) %>%
  distinct();

Plot data

Plot data: all fermentation products

plot.ferm = ggplot(data.samples, aes(
   x = Compound, 
   y = Concentration_mean, 
   fill = Compound))+
 geom_violin()+
 geom_jitter(aes(color=Compound, text = Sample), size = 2, position=position_jitter(0.2))+
 xlab("Compound")+
 ylab("mM produced")+
 coord_cartesian(ylim=c(0, 50))+
 scale_y_continuous(breaks=seq(0, 50, 10))+
 #scale_color_manual(values = c('gray', '#613f4f', 'red', 'green', 'blue'))+
 theme_classic()+
 mytheme;

plotly.ferm = ggplotly(plot.ferm, tooltip="text");
plotly.ferm

Fig 1: Fermentation products by C.phytofermentans PHY24.0 clones growing in GS2 medium with no addition.

Conclusions